One facet is explaining a suggested decision made by an computer system and what justification supports it to the medical provider who is diagnosing a malady.
&nbsp&nbsp&nbsp&nbsp(2B)

Another is explaining a medical process to the patient who might be a participant and their support team.
&nbsp&nbsp&nbsp&nbsp(2C)

Similarly, there is the explanation and justification to the billed party of such a process and why it is coded the way it is, whether that billed party is the patient, an insurance company or some other financier.
&nbsp&nbsp&nbsp&nbsp(2D)

[12:05] DavidWhitten: Many of the current AI efforts are using neural networks to train recognition of data and patterns in data.
&nbsp&nbsp&nbsp&nbsp(2I2)

[12:07] DavidWhitten: The hope is that an explainable system would help doctors reconciling a diagnosis and matching it up against the data in the medical record.
&nbsp&nbsp&nbsp&nbsp(2I3)

[12:09] DavidWhitten: There are some great advantages in recognizing a diagnosis as early as possible. Perhaps using the automated pathology to look at cells to help look for irregularities that might indicate cancer etc.
&nbsp&nbsp&nbsp&nbsp(2I4)

[12:10] DavidWhitten: Processing a medical record involves recognizing pre-defined fields and data as well as using natural language processing on notes about patients from providers.
&nbsp&nbsp&nbsp&nbsp(2I5)

[12:11] DavidWhitten: Augie works with Data Warehousing in the VA, which gets an almost realtime (within 5 minutes or so) data sample size quickly from the providers interactions with patients
&nbsp&nbsp&nbsp&nbsp(2I6)

[12:13] DavidWhitten: explanations from neural nets require recognition of features and tying them to neural nets local levels of the net.
&nbsp&nbsp&nbsp&nbsp(2I7)

[12:13] Gary: Shadows are good examples of phenomena that humans experience embedded in the world and have to interpret them while artificial systems do not typically get this "experience".
&nbsp&nbsp&nbsp&nbsp(2I8)

[12:17] DavidWhitten: It is easy to build in biases in the neural net's classifications that if your data that trains the neural net is heavily weighted in some dimension, such as most data is related to males can generate gender biased nets.
&nbsp&nbsp&nbsp&nbsp(2I9)

[12:41] DavidWhitten: The VA record system has ties between an encounter with the patients and standard coding systems such as ICD9, ICD10, CPT, SNOMED CT, etc.
&nbsp&nbsp&nbsp&nbsp(2I22)

[12:42] Gary: Have the difficulties with this effort been documented and published with lesson learned??
&nbsp&nbsp&nbsp&nbsp(2I23)

[12:44] DavidWhitten: I expect that most information is anecdotal. When a system is going well, it is easy to find resources to document and publish. When a system doesn't meet expectations, it is much harder to find the resources.
&nbsp&nbsp&nbsp&nbsp(2I24)

[12:45] RaviSharma: Augie - Does a set of genes correlate with behavior type? then what is the indicator of changed behavior or mood swing, is it dynamics in Gene or is it jumping genes?
&nbsp&nbsp&nbsp&nbsp(2I26)